Digital watermarking is a process for modifying physical or electronic media to embed a hidden machine-readable code into the media. The media may be modified such that the embedded code is imperceptible or nearly imperceptible to the user, yet may be detected through an automated detection process. Most commonly, digital watermarking is applied to media signals such as images, audio signals, and video signals. However, it may also be applied to other types of media objects, including documents (e.g., through line, word or character shifting), software, multi-dimensional graphics models, and surface textures of objects.
Digital watermarking systems typically have two primary components: an encoder that embeds the watermark in a host media signal, and a decoder that detects and reads the embedded watermark from a signal suspected of containing a watermark (a suspect signal). The encoder embeds a watermark by subtly altering the host media signal. The reading component analyzes a suspect signal to detect whether a watermark is present. In applications where the watermark encodes information, the reader extracts this information from the detected watermark.
Several particular watermarking techniques have been developed. The reader is presumed to be familiar with the literature in this field. Particular techniques for embedding and detecting imperceptible watermarks in media signals are detailed in the assignee's co-pending application Ser. No. 09/503,881 (now U.S. Pat. No. 6,614,914) and U.S. Pat. No. 6,122,403, which are herein incorporated by reference.
The disclosure describes methods for adaptive prediction filtering for digital watermarking applications. The predictive filter is designed to predict the digital watermark signal. In one implementation, there are two stages of prediction filtering. A first stage operates on a suspect signal before detecting any watermark in that signal. This stage adapts the predictive filter to local image characteristics. A second stage uses known watermark signal elements to adapt a non-linear filter used in extracting message symbols from the suspect signal. This stage produces detection statistics based on a comparison of expected and measured message symbol values, and uses these statistics to adapt the parameters of a predictive filter. This adapted prediction filter is then applied to extract message symbol estimates.
In one implementation, the first adaptive filter stage selects a filter for use in detecting a watermark and determining geometric synchronization. The second adaptive filter selects a filter (e.g., non-linear filter parameters) for use in extracting values of unknown message symbols from the variable portion of a digital watermark signal. The results produced in analyzing the known watermark signal may be used to refine the adaptive filter used in the geometric synchronization stage. In addition, the results produced in analyzing the known watermark signal may be used to as an indicator of watermark signal reliability to isolate areas of the suspect signal in which to perform watermark synchronization and message signal extraction.
The watermark embedder may be designed for a particular application by training the embedder on a test set of signal content with known watermark signals. Using the known signals, the training program can derive the appropriate non-linear embedding function and corresponding prediction filter. The non-linear embedding function for images, for example, adjusts each pixel relative to its neighbors so as to optimize the chances of accurate message symbol recovery as a function of the corresponding non-linear prediction filter and perceptual quality constraints.
Finally, the above techniques may be used to optimize and detect fragile watermarks to detect host signal alteration and copying.
Further features will become apparent with reference to the following detailed description.